# A Computational Approach for the Prediction of p53 and BCL-2 Protein–Protein Interactions

**Authors:** Colette Creamer, Victoria Neely, Hisashi Harada

PMC · DOI: 10.3390/ijms27010244 · International Journal of Molecular Sciences · 2025-12-25

## TL;DR

This paper presents a computational method to predict how wild-type and mutant p53 proteins interact with BCL-2, which could help understand cell survival and death mechanisms.

## Contribution

The novel contribution is a predictive computational workflow for p53-BCL-2 interactions using full-length proteins and wild-type sequences.

## Key findings

- The protocol successfully replicated known amino acid interactions from previous studies.
- Most major mutant p53 variants interact with BCL-2 but with reduced affinity compared to wild-type p53.
- The method could inform future in vitro and in vivo studies on p53-BCL-2 interactions.

## Abstract

p53 has long been studied as a major regulator in cellular pathways, resulting in a plethora of information on the structure and function of this protein as a frequently mutated tumor suppressor. Recent studies have demonstrated how the p53 transcription activation domain (TAD) interacts with the BH3-binding pocket of BCL-2 to regulate cell survival/death. While the in vitro studies on p53 and BCL-2 have frequently used truncated and stabilized proteins of p53 to ensure crystallization, these mutated proteins are not naturally observed in cells. Thus, it becomes important to find a way in silico to simulate how a full-length monomer with the unaltered sequence of wild-type (WT) or missense mutant (MT) p53 interacts with BCL-2. Our objective is to provide a predictive insight into how p53 monomers might interact with BCL-2 through the combination of previously published algorithms. Using pre-established computational techniques in silico, the interactions between p53 variants and BCL-2 were compared to existing crystals to ensure the validity of the current method, and the affinities were predicted to explore the strength of these interactions. Here, we found that this protocol was able to replicate some of the amino acid interactions identified in the previous literature, as well as identify affinities between each WT/MT p53 and BCL-2. Most major MT p53 variants are predicted to directly interact with BCL-2, but have a decrease in affinity compared to WT p53, suggesting a potential increase in BCL-2 survival activity. Together, the method described here can potentially be useful as a predictive workflow to inform future studies in vitro and in vivo.

## Linked entities

- **Genes:** TP53 (tumor protein p53) [NCBI Gene 7157], BCL2 (BCL2 apoptosis regulator) [NCBI Gene 596]
- **Proteins:** TP53 (tumor protein p53), BCL2 (BCL2 apoptosis regulator)

## Full-text entities

- **Genes:** BCL2 (BCL2 apoptosis regulator) [NCBI Gene 596] {aka Bcl-2, PPP1R50}, TP53 (tumor protein p53) [NCBI Gene 7157] {aka BCC7, BMFS5, LFS1, P53, TRP53}
- **Diseases:** tumor (MESH:D009369)

## Full text

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## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12785448/full.md

## References

46 references — full list in the complete paper: https://tomesphere.com/paper/PMC12785448/full.md

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Source: https://tomesphere.com/paper/PMC12785448